Image-To-Image Translation. A lot of recently developed models have focused on image-to-image translation, i.e. to learn the mapping between an input and an output image in a way that the content of the original input image is preserved while characteristics of output image are applied. This includes CycleGAN [1]}, pix2pix [2]}, MUNIT [3]}, DRIT [4]}, DistanceGAN and SelfDistance [5]}, GCGAN [6]}, etc. More detailed comparisons and explanations of different implementations available to date can be found in Image-to-Image Translation: Methods and Applications [7]}.
